A Context-Aware Conversational Agent in the Rehabilitation Domain

Thanassis Mavropoulos, Georgios Meditskos, Spyridon Symeonidis, Eleni Kamateri, Maria Rousi, Dimitris Tzimikas, Lefteris Papageorgiou, Christos Eleftheriadis, George Adamopoulos, Stefanos Vrochidis and Ioannis Kompatsiaris
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Thanassis Mavropoulos: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Georgios Meditskos: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Spyridon Symeonidis: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Eleni Kamateri: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Maria Rousi: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Dimitris Tzimikas: Entranet Ltd., 54249 Thessaloniki, Greece
Lefteris Papageorgiou: Entranet Ltd., 54249 Thessaloniki, Greece
Christos Eleftheriadis: ELBIS P.C., 57001 Thessaloniki, Greece
George Adamopoulos: Evexia S.A., 63080 Thessaloniki, Greece
Stefanos Vrochidis: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Ioannis Kompatsiaris: Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece

Future Internet, 2019, vol. 11, issue 11, 1-20

Abstract: Conversational agents are reshaping our communication environment and have the potential to inform and persuade in new and effective ways. In this paper, we present the underlying technologies and the theoretical background behind a health-care platform dedicated to supporting medical stuff and individuals with movement disabilities and to providing advanced monitoring functionalities in hospital and home surroundings. The framework implements an intelligent combination of two research areas: (1) sensor- and camera-based monitoring to collect, analyse, and interpret people behaviour and (2) natural machine–human interaction through an apprehensive virtual assistant benefiting ailing patients. In addition, the framework serves as an important assistant to caregivers and clinical experts to obtain information about the patients in an intuitive manner. The proposed approach capitalises on latest breakthroughs in computer vision, sensor management, speech recognition, natural language processing, knowledge representation, dialogue management, semantic reasoning, and speech synthesis, combining medical expertise and patient history.

Keywords: wireless sensor networks; ontology-based dialogue management; semantic disambiguation; natural language processing; virtual assistant (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2019
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